{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This mounts your Google Drive to the Colab VM.\n",
    "from google.colab import drive\n",
    "drive.mount('/content/drive', force_remount=True)\n",
    "\n",
    "# Enter the foldername in your Drive where you have saved the unzipped\n",
    "# assignment folder, e.g. 'cs231n/assignments/assignment1/'\n",
    "FOLDERNAME = None\n",
    "assert FOLDERNAME is not None, \"[!] Enter the foldername.\"\n",
    "\n",
    "# Now that we've mounted your Drive, this ensures that\n",
    "# the Python interpreter of the Colab VM can load\n",
    "# python files from within it.\n",
    "import sys\n",
    "sys.path.append('/content/drive/My Drive/{}'.format(FOLDERNAME))\n",
    "\n",
    "# This downloads the CIFAR-10 dataset to your Drive\n",
    "# if it doesn't already exist.\n",
    "%cd drive/My\\ Drive/$FOLDERNAME/cs231n/datasets/\n",
    "!bash get_datasets.sh\n",
    "%cd /content/drive/My\\ Drive/$FOLDERNAME"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-title"
    ]
   },
   "source": [
    "# Multiclass Support Vector Machine exercise\n",
    "\n",
    "*Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For more details see the [assignments page](http://vision.stanford.edu/teaching/cs231n/assignments.html) on the course website.*\n",
    "\n",
    "In this exercise you will:\n",
    "    \n",
    "- implement a fully-vectorized **loss function** for the SVM\n",
    "- implement the fully-vectorized expression for its **analytic gradient**\n",
    "- **check your implementation** using numerical gradient\n",
    "- use a validation set to **tune the learning rate and regularization** strength\n",
    "- **optimize** the loss function with **SGD**\n",
    "- **visualize** the final learned weights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "# Run some setup code for this notebook.\n",
    "import random\n",
    "import numpy as np\n",
    "from cs231n.data_utils import load_CIFAR10\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# This is a bit of magic to make matplotlib figures appear inline in the\n",
    "# notebook rather than in a new window.\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# Some more magic so that the notebook will reload external python modules;\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "source": [
    "## CIFAR-10 Data Loading and Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (50000, 32, 32, 3)\n",
      "Training labels shape:  (50000,)\n",
      "Test data shape:  (10000, 32, 32, 3)\n",
      "Test labels shape:  (10000,)\n"
     ]
    }
   ],
   "source": [
    "# Load the raw CIFAR-10 data.\n",
    "cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "\n",
    "# Cleaning up variables to prevent loading data multiple times (which may cause memory issue)\n",
    "try:\n",
    "   del X_train, y_train\n",
    "   del X_test, y_test\n",
    "   print('Clear previously loaded data.')\n",
    "except:\n",
    "   pass\n",
    "\n",
    "X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "\n",
    "# As a sanity check, we print out the size of the training and test data.\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Training labels shape: ', y_train.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 70 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize some examples from the dataset.\n",
    "# We show a few examples of training images from each class.\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "num_classes = len(classes)\n",
    "samples_per_class = 7\n",
    "for y, cls in enumerate(classes):\n",
    "    idxs = np.flatnonzero(y_train == y)\n",
    "    idxs = np.random.choice(idxs, samples_per_class, replace=False)\n",
    "    for i, idx in enumerate(idxs):\n",
    "        plt_idx = i * num_classes + y + 1\n",
    "        plt.subplot(samples_per_class, num_classes, plt_idx)\n",
    "        plt.imshow(X_train[idx].astype('uint8'))\n",
    "        plt.axis('off')\n",
    "        if i == 0:\n",
    "            plt.title(cls)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 32, 32, 3)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 32, 32, 3)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 32, 32, 3)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "# Split the data into train, val, and test sets. In addition we will\n",
    "# create a small development set as a subset of the training data;\n",
    "# we can use this for development so our code runs faster.\n",
    "num_training = 49000\n",
    "num_validation = 1000\n",
    "num_test = 1000\n",
    "num_dev = 500\n",
    "\n",
    "# 验证集\n",
    "# Our validation set will be num_validation points from the original\n",
    "# training set.\n",
    "mask = range(num_training, num_training + num_validation)\n",
    "X_val = X_train[mask]\n",
    "y_val = y_train[mask]\n",
    "\n",
    "# 训练集\n",
    "# Our training set will be the first num_train points from the original\n",
    "# training set.\n",
    "mask = range(num_training)\n",
    "X_train = X_train[mask]\n",
    "y_train = y_train[mask]\n",
    "\n",
    "# 训练集子集\n",
    "# We will also make a development set, which is a small subset of\n",
    "# the training set.\n",
    "mask = np.random.choice(num_training, num_dev, replace=False)\n",
    "X_dev = X_train[mask]\n",
    "y_dev = y_train[mask]\n",
    "\n",
    "# 测试集\n",
    "# We use the first num_test points of the original test set as our\n",
    "# test set.\n",
    "mask = range(num_test)\n",
    "X_test = X_test[mask]\n",
    "y_test = y_test[mask]\n",
    "\n",
    "print('Train data shape: ', X_train.shape)\n",
    "print('Train labels shape: ', y_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Validation labels shape: ', y_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (49000, 3072)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Test data shape:  (1000, 3072)\n",
      "dev data shape:  (500, 3072)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: reshape the image data into rows\n",
    "X_train = np.reshape(X_train, (X_train.shape[0], -1))\n",
    "X_val = np.reshape(X_val, (X_val.shape[0], -1))\n",
    "X_test = np.reshape(X_test, (X_test.shape[0], -1))\n",
    "X_dev = np.reshape(X_dev, (X_dev.shape[0], -1))\n",
    "\n",
    "# As a sanity check, print out the shapes of the data\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('dev data shape: ', X_dev.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[130.64189796 135.98173469 132.47391837 130.05569388 135.34804082\n",
      " 131.75402041 130.96055102 136.14328571 132.47636735 131.48467347]\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPsAAAD5CAYAAADhukOtAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAARvklEQVR4nO3db6hl1XnH8e8vRhvvVfxToxlUOon4oiLNKJdBsARb2zCVgPpCiS/CvJBMSiNUSF8MFqp9Z0s1CC2WsQ6ZFGuUqihF2siQIoFivVodx07aGJmaqcOMqYp2bmiq8/TF2QPX6d3rnPOcvfc5un4fGO45e5+113P3nOfuc/dz11qKCMzsk+9T8w7AzIbhZDerhJPdrBJOdrNKONnNKuFkN6vEp2dpLGkbcB9wCvBXEXF36fXLy8tx9jlnz9LlADR9i+mb2JzlK86LXap+9513OXbs2IbvyHSySzoF+Avgt4FDwPOSnoqIf21rc/Y5Z/O7t/1ey97CSWzJplKOKZmBmXblJu07k80WR8fv+/zhpm+ZTfbs36WU2rXuSfT1l39+f+u+WT7GbwVei4jXI+IXwPeA62c4npn1aJZkvxD46brnh5ptZraAZkn2jT5o/r/PHZJ2SFqVtHrs2LEZujOzWcyS7IeAi9c9vwh48+QXRcSuiFiJiJXl5eUZujOzWcyS7M8Dl0r6vKTTgK8CT3UTlpl1LX03PiI+kHQb8A+MSm+7I+LVCVq2Ha+1hdralG5Zl+5klu50R2Fn265im+xt31yzT6quK2WRPGLxbnxuV3ssHb8HZqqzR8TTwNMdxWJmPfJf0JlVwsluVgknu1klnOxmlXCym1ViprvxGW2li4jjhUYtpa10WStZKmvbVRgJUzxcL4NdWuuDhUD6iGM4mfDTA1qS57HYW6o8uPH/c+nb8pXdrBJOdrNKONnNKuFkN6uEk92sEoPfjW+/9ZgYuJK8+9k2sGZsGImBMMU77sVvOXurPjFFU6HNcFFkG2UPmdlT3pkNv9uBMO2NfGU3q4ST3awSTnazSjjZzSrhZDerhJPdrBLDlt4iCrWtUjls4319lIWKlbLMgJz0VHjJml2mt8xqJT3oo6+u53fLl9eG66uNr+xmlXCym1XCyW5WCSe7WSWc7GaVcLKbVWKm0pukg8D7wIfABxGxUnp9UJqDbvqRV+XSxIBFo+xkcl1X17L66Cv3n9aq6xD7KfMN2W76Vl3U2X8jIn7WwXHMrEf+GG9WiVmTPYDvS3pB0o4uAjKzfsz6Mf7qiHhT0vnAM5J+FBHPrn9B80NgB8BZZ501Y3dmljXTlT0i3my+HgWeALZu8JpdEbESEStLy0uzdGdmM0gnu6RlSWeeeAx8GdjfVWBm1q1ZPsZfADyh0eisTwN/ExF/P77Z9BNOlpfBma4byFe82iaqjMIRyyPbCjsXRXqI4HBxpLpKnvthy2vdvkHSyR4RrwNf7DAWM+uRS29mlXCym1XCyW5WCSe7WSWc7GaVGHytt4jjU20vH6x9V3E9t+l7ygfSQ7POLUp5rQetIWZjL0wE2n1ZLrXwYGsTX9nNKuFkN6uEk92sEk52s0o42c0qMfDd+PblnzJz0OWXLSr01fWAi4F1PrZmyKn8+jho4oSUBjaV3nPFZtOHkR5g1cZXdrNKONnNKuFkN6uEk92sEk52s0o42c0qMfhAmNbSRWYOuuRAmJJSZaWtw+JYkeRceFlt3aX7Kjbs+jvoofjWMtFfef6/3MigYeenm/5gvrKbVcLJblYJJ7tZJZzsZpVwsptVwsluVomxpTdJu4GvAEcj4vJm27nAI8Bm4CBwc0S8M0mH7Us5lYabTd8mX/LKDHvLDZXLTv2W08d6RwPXFaePYuzejZXKa8mSbuqElMrR0x9vkiv7d4BtJ23bCeyNiEuBvc1zM1tgY5O9WW/97ZM2Xw/saR7vAW7oNiwz61r2d/YLIuIwQPP1/O5CMrM+9H6DTtIOSauSVteOrfXdnZm1yCb7EUmbAJqvR9teGBG7ImIlIlaWlpeS3ZnZrLLJ/hSwvXm8HXiym3DMrC+TlN4eBq4BzpN0CLgTuBt4VNKtwBvATRP1FhQmnGxf/ql9Esjs7JDdLteUmixzcH1M55iYYTF9QjouVJbeOqVZR7OzShaOmXn3tK9C1X60sckeEbe07Lp2XFszWxz+CzqzSjjZzSrhZDerhJPdrBJOdrNKfDwmnCzPArkhJdeBS81DmIivL8OW+rouh+XOo4plrZY4irOElnor9NVeD8t9a+kYN+Yru1klnOxmlXCym1XCyW5WCSe7WSWc7GaVGLj0FgQto9tKtYlBJ5ws6LjEVhpcVajidD6ArZ9yXcvoxmQc+UGMnQ+/K3SVe9O1lQe7fgv4ym5WCSe7WSWc7GaVcLKbVcLJblaJhRkIUx7ssvG+0mCXcgypXag1jlwYJelqQiKW/PJJizHDXub0F99viTvn4+IovlVb3kClvqTpr9O+sptVwsluVgknu1klnOxmlXCym1XCyW5WiUmWf9oNfAU4GhGXN9vuAr4OvNW87I6IeHq2UKYfCJNddqlcdZm+kJM9Xra8tjjFsG7rfNMXXxuJFZlKZa3s0lDlszF9ya5cYp3+3E9yZf8OsG2D7d+OiC3NvxkT3cz6NjbZI+JZ4O0BYjGzHs3yO/ttkvZJ2i3pnM4iMrNeZJP9fuASYAtwGLin7YWSdkhalbS6traW7M7MZpVK9og4EhEfxmhR9QeArYXX7oqIlYhYWVpaysZpZjNKJbukTeue3gjs7yYcM+vLJKW3h4FrgPMkHQLuBK6RtIVR1eAg8I2Je0ws/5RaMqoQQnZpqPZGyXpS+aCFfYnCXB8hdi1XDUt9b8XSWymOYlmu24JpZgRmqdXYZI+IWzbY/OC4dma2WPwXdGaVcLKbVcLJblYJJ7tZJZzsZpUYfsLJ1mWBui29pctyXdeoepgUs7jsVeaA6RAT5cEelrXKlNFKsZcnhyyMXisOY5x+PGKpSSYlfGU3q4ST3awSTnazSjjZzSrhZDerhJPdrBJzKL21KJXKWusMxwvHy/WVkh59Vzhksg7VVq0pf8t9jHtLjL5LlKfGHbT1+y6V0Eo9dVxeK4rCWm+J/zNf2c0q4WQ3q4ST3awSTnazSjjZzSox8N34SN0Jb78bnxsIkx8k07I9O2gleRO8PJbkYzwHXfJOd2p8UnKOvz7OVfu31m1vvrKbVcLJblYJJ7tZJZzsZpVwsptVwsluVolJln+6GPgu8DngOLArIu6TdC7wCLCZ0RJQN0fEO9lAigMM2uat66H0lpEeZFKqNOWO2L53QeprhbEdYxp23F/XxxtzzPJ8chvvLJ+qfgbCfAB8KyJ+FbgK+Kaky4CdwN6IuBTY2zw3swU1Ntkj4nBEvNg8fh84AFwIXA/saV62B7ihpxjNrANT/c4uaTNwBfAccEFEHIbRDwTg/M6jM7POTJzsks4AHgNuj4j3pmi3Q9KqpNW1Yz/PxGhmHZgo2SWdyijRH4qIx5vNRyRtavZvAo5u1DYidkXESkSsLC2f3kXMZpYwNtklidF67Aci4t51u54CtjePtwNPdh+emXVlklFvVwNfA16R9FKz7Q7gbuBRSbcCbwA39RJhUqKSN8nOjgNJRpEo2ZWX1yr01fG0auW+ul8bqv30l5aM6v5clQf0Zb636f9jxiZ7RPywcORrp+7RzObCf0FnVgknu1klnOxmlXCym1XCyW5WicVZ/qk4MWPLqLfs8dJlnI3bdV2dajrLNZt6R/aAScXq2nBLK2UnnMzKHTFdP96Qr+xmlXCym1XCyW5WCSe7WSWc7GaVcLKbVWKBSm/txYm2qkvH80aeOGrHLRZkpsc+lAaOJQ5XHumXnJ0zE0m6BDhsOW9avrKbVcLJblYJJ7tZJZzsZpVwsptVYmHuxheXxynMrNbaZuBlhtotSCAD3wxemNM41PHGHbTUX+u+QoUq0Y2v7GaVcLKbVcLJblYJJ7tZJZzsZpVwsptVYmzpTdLFwHeBzwHHgV0RcZ+ku4CvA281L70jIp4e22Om5NHSpjwmoX1nuiyUWqanoI+lkFp2LcpwnPxUch2PukkfrzRgq9t9HU+7N1Gd/QPgWxHxoqQzgRckPdPs+3ZE/Fm3IZlZHyZZ6+0wcLh5/L6kA8CFfQdmZt2a6nd2SZuBK4Dnmk23Sdonabekc7oOzsy6M3GySzoDeAy4PSLeA+4HLgG2MLry39PSboekVUmra2s/nz1iM0uZKNklncoo0R+KiMcBIuJIRHwYEceBB4CtG7WNiF0RsRIRK0tLp3cVt5lNaWyya3Sr8EHgQETcu277pnUvuxHY3314ZtaVSe7GXw18DXhF0kvNtjuAWyRtYVTVOQh8Y7ZQSiN8pq+9RaFMVi5qDTk8LFkQKw3pa92VOx9liZY9nN5SWSt5wGS70iEzZbniAaduMsnd+B+2HGJ8Td3MFob/gs6sEk52s0o42c0q4WQ3q4ST3awSH48JJzMT8vVQPmmVHVJW/KYLk2kmgmktX85k+mOmq2Sl0lWxXapVLo7svpZYuq4o+spuVgknu1klnOxmlXCym1XCyW5WCSe7WSUGL71lCiiZMpo+1f5zLAplLRUnc5x+pFFRqbxWKtUUy3Ld1ms6L9gl60ndl1KzcaQ6G1OWS7QphdHCV3azSjjZzSrhZDerhJPdrBJOdrNKONnNKjFw6U20FQ0yJY3yUm+50lVqCFt6IbVCCa2HYw4rMyKuj5GKHZcis30lSm9jIpm6ha/sZpVwsptVwsluVgknu1klnOxmlRh7N17SZ4BngV9qXv+3EXGnpHOBR4DNjJZ/ujki3hl/vNZ+SjFsuL08oKWkNNil2LBjixLHgNI33DNLXvUQSFbHFYPMHfxJruz/A/xmRHyR0fLM2yRdBewE9kbEpcDe5rmZLaixyR4j/908PbX5F8D1wJ5m+x7ghj4CNLNuTLo++ynNCq5HgWci4jnggog4DNB8Pb+3KM1sZhMle0R8GBFbgIuArZIun7QDSTskrUpaXVtbS4ZpZrOa6m58RLwL/COwDTgiaRNA8/VoS5tdEbESEStLS0uzRWtmaWOTXdJnJZ3dPD4d+C3gR8BTwPbmZduBJ3uK0cw6MMlAmE3AHkmnMPrh8GhE/J2kfwIelXQr8AZw02Rdtg2E6XbgxMCFlR7UV3sbcDxLP2c3edBcs7YT0n6ixiZ7ROwDrthg+38B104ampnNl/+CzqwSTnazSjjZzSrhZDerhJPdrBIqjRzrvDPpLeA/mqfnAT8brPN2juOjHMdHfdzi+JWI+OxGOwZN9o90LK1GxMpcOnccjqPCOPwx3qwSTnazSswz2XfNse/1HMdHOY6P+sTEMbff2c1sWP4Yb1aJuSS7pG2S/k3Sa5LmNnedpIOSXpH0kqTVAfvdLemopP3rtp0r6RlJP26+njOnOO6S9J/NOXlJ0nUDxHGxpB9IOiDpVUm/32wf9JwU4hj0nEj6jKR/lvRyE8cfN9tnOx8RMeg/4BTgJ8AXgNOAl4HLho6jieUgcN4c+v0ScCWwf922PwV2No93An8ypzjuAv5g4POxCbiyeXwm8O/AZUOfk0Icg54TRuNUz2genwo8B1w16/mYx5V9K/BaRLweEb8Avsdo8spqRMSzwNsnbR58As+WOAYXEYcj4sXm8fvAAeBCBj4nhTgGFSOdT/I6j2S/EPjpuueHmMMJbQTwfUkvSNoxpxhOWKQJPG+TtK/5mN/7rxPrSdrMaP6EuU5qelIcMPA56WOS13kk+0ZTacyrJHB1RFwJ/A7wTUlfmlMci+R+4BJGawQcBu4ZqmNJZwCPAbdHxHtD9TtBHIOfk5hhktc280j2Q8DF655fBLw5hziIiDebr0eBJxj9ijEvE03g2beIONK80Y4DDzDQOZF0KqMEeygiHm82D35ONopjXuek6ftdppzktc08kv154FJJn5d0GvBVRpNXDkrSsqQzTzwGvgzsL7fq1UJM4HnizdS4kQHOiUaTCT4IHIiIe9ftGvSctMUx9DnpbZLXoe4wnnS38TpGdzp/AvzhnGL4AqNKwMvAq0PGATzM6OPg/zL6pHMr8MuMltH6cfP13DnF8dfAK8C+5s21aYA4fp3Rr3L7gJeaf9cNfU4KcQx6ToBfA/6l6W8/8EfN9pnOh/+CzqwS/gs6s0o42c0q4WQ3q4ST3awSTnazSjjZzSrhZDerhJPdrBL/B8c/hMGb+vGCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(49000, 3073) (1000, 3073) (1000, 3073) (500, 3073)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: subtract the mean image\n",
    "# first: compute the image mean based on the training data\n",
    "mean_image = np.mean(X_train, axis=0)\n",
    "print(mean_image[:10]) # print a few of the elements\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.imshow(mean_image.reshape((32,32,3)).astype('uint8')) # visualize the mean image\n",
    "plt.show()\n",
    "\n",
    "# second: subtract the mean image from train and test data\n",
    "X_train -= mean_image\n",
    "X_val -= mean_image\n",
    "X_test -= mean_image\n",
    "X_dev -= mean_image\n",
    "\n",
    "# third: append the bias dimension of ones (i.e. bias trick) so that our SVM\n",
    "# only has to worry about optimizing a single weight matrix W.\n",
    "X_train = np.hstack([X_train, np.ones((X_train.shape[0], 1))])\n",
    "X_val = np.hstack([X_val, np.ones((X_val.shape[0], 1))])\n",
    "X_test = np.hstack([X_test, np.ones((X_test.shape[0], 1))])\n",
    "X_dev = np.hstack([X_dev, np.ones((X_dev.shape[0], 1))])\n",
    "\n",
    "print(X_train.shape, X_val.shape, X_test.shape, X_dev.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SVM Classifier\n",
    "\n",
    "Your code for this section will all be written inside `cs231n/classifiers/linear_svm.py`. \n",
    "\n",
    "As you can see, we have prefilled the function `svm_loss_naive` which uses for loops to evaluate the multiclass SVM loss function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss: 9.104668\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the naive implementation of the loss we provided for you:\n",
    "from cs231n.classifiers.linear_svm import svm_loss_naive\n",
    "import time\n",
    "\n",
    "# generate a random SVM weight matrix of small numbers\n",
    "W = np.random.randn(3073, 10) * 0.0001 \n",
    "\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "print('loss: %f' % (loss, ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `grad` returned from the function above is right now all zero. Derive and implement the gradient for the SVM cost function and implement it inline inside the function `svm_loss_naive`. You will find it helpful to interleave your new code inside the existing function.\n",
    "\n",
    "To check that you have correctly implemented the gradient correctly, you can numerically estimate the gradient of the loss function and compare the numeric estimate to the gradient that you computed. We have provided code that does this for you:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1e-05\n",
      "numerical: -48.886461 analytic: -48.886461, relative error: 4.711011e-12\n",
      "numerical: 10.723875 analytic: 10.719133, relative error: 2.211266e-04\n",
      "numerical: 11.600088 analytic: 11.622428, relative error: 9.619850e-04\n",
      "numerical: -3.129819 analytic: -3.129819, relative error: 3.365340e-11\n",
      "numerical: 29.627640 analytic: 29.610171, relative error: 2.948809e-04\n",
      "numerical: 1.450246 analytic: 1.450246, relative error: 2.409325e-10\n",
      "numerical: 1.196453 analytic: 1.196453, relative error: 1.608794e-10\n",
      "numerical: -22.993977 analytic: -23.082320, relative error: 1.917314e-03\n",
      "numerical: 42.149261 analytic: 42.131174, relative error: 2.146014e-04\n",
      "numerical: 2.601861 analytic: 2.540604, relative error: 1.191204e-02\n",
      "1e-05\n",
      "numerical: 11.914734 analytic: 11.914592, relative error: 5.962840e-06\n",
      "numerical: 11.814821 analytic: 11.800828, relative error: 5.925175e-04\n",
      "numerical: -10.491476 analytic: -10.582433, relative error: 4.316111e-03\n",
      "numerical: -2.468398 analytic: -2.481531, relative error: 2.653316e-03\n",
      "numerical: -10.564979 analytic: -10.588477, relative error: 1.110829e-03\n",
      "numerical: -45.057181 analytic: -45.046659, relative error: 1.167736e-04\n",
      "numerical: 26.699032 analytic: 26.703377, relative error: 8.135057e-05\n",
      "numerical: 48.273955 analytic: 48.241762, relative error: 3.335564e-04\n",
      "numerical: 14.742661 analytic: 14.854117, relative error: 3.765820e-03\n",
      "numerical: 8.361086 analytic: 8.422172, relative error: 3.639705e-03\n"
     ]
    }
   ],
   "source": [
    "# Once you've implemented the gradient, recompute it with the code below\n",
    "# and gradient check it with the function we provided for you\n",
    "\n",
    "# Compute the loss and its gradient at W.\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.0)\n",
    "\n",
    "# Numerically compute the gradient along several randomly chosen dimensions, and\n",
    "# compare them with your analytically computed gradient. The numbers should match\n",
    "# almost exactly along all dimensions.\n",
    "from cs231n.gradient_check import grad_check_sparse\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 0.0)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)\n",
    "\n",
    "# do the gradient check once again with regularization turned on\n",
    "# you didn't forget the regularization gradient did you?\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 5e1)\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 5e1)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Inline Question 1**\n",
    "\n",
    "It is possible that once in a while a dimension in the gradcheck will not match exactly. What could such a discrepancy be caused by? Is it a reason for concern? What is a simple example in one dimension where a gradient check could fail? How would change the margin affect of the frequency of this happening? *Hint: the SVM loss function is not strictly speaking differentiable*\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$ 数值梯度通过数值方法求得梯度，只有h非常小时它的结果才是近似精确的；而分析梯度从解析式求得梯度，它的结果应是严格经确的，仅有数字截断误差。\n",
    "\n",
    "由于SVM使用的误差函数为Relu，它在x=0不可微，因此在此点附近数值、解析梯度的差异会较大，如：\n",
    "\n",
    "ReLU: $f(x) = max(0,x)$\n",
    "\n",
    "数值梯度: $\\frac{df(x)}{dx} = \\frac{f(x+h)-f(x-h)}{2*h}$\n",
    "\n",
    "解析梯度：$\\frac{df(x)}{dx} = \\begin{cases}1,&x>0 \\\\ 不存在,&x=0 \\\\ 0, &x<0 \\end{cases}$\n",
    "\n",
    "当: $x = \\frac{h}{2}$ 时,数值梯度：$\\frac{df(x)}{dx} = \\frac{3}{4}$，解析梯度: $\\frac{df(x)}{dx} = 1$。从而数值梯度、解析梯度出现较大误差。\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "id": "vectorized_time_1",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss: 9.104668e+00 computed in 0.118380s\n",
      "Vectorized loss: 0.000000e+00 computed in 0.000000s\n",
      "difference: 9.104668\n"
     ]
    }
   ],
   "source": [
    "# Next implement the function svm_loss_vectorized; for now only compute the loss;\n",
    "# we will implement the gradient in a moment.\n",
    "tic = time.time()\n",
    "loss_naive, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss: %e computed in %fs' % (loss_naive, toc - tic))\n",
    "\n",
    "from cs231n.classifiers.linear_svm import svm_loss_vectorized\n",
    "tic = time.time()\n",
    "loss_vectorized, _ = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss: %e computed in %fs' % (loss_vectorized, toc - tic))\n",
    "\n",
    "# The losses should match but your vectorized implementation should be much faster.\n",
    "print('difference: %f' % (loss_naive - loss_vectorized))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "id": "vectorized_time_2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.104668331193384\n",
      "Naive loss and gradient: computed in 0.125494s\n",
      "Vectorized loss and gradient: computed in 0.003991s\n",
      "difference: 0.000000\n"
     ]
    }
   ],
   "source": [
    "# Complete the implementation of svm_loss_vectorized, and compute the gradient\n",
    "# of the loss function in a vectorized way.\n",
    "\n",
    "# The naive implementation and the vectorized implementation should match, but\n",
    "# the vectorized version should still be much faster.\n",
    "tic = time.time()\n",
    "_, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "tic = time.time()\n",
    "_, grad_vectorized = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "# The loss is a single number, so it is easy to compare the values computed\n",
    "# by the two implementations. The gradient on the other hand is a matrix, so\n",
    "# we use the Frobenius norm to compare them.\n",
    "difference = np.linalg.norm(grad_naive - grad_vectorized, ord='fro')\n",
    "print('difference: %f' % difference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stochastic Gradient Descent\n",
    "\n",
    "We now have vectorized and efficient expressions for the loss, the gradient and our gradient matches the numerical gradient. We are therefore ready to do SGD to minimize the loss. Your code for this part will be written inside `cs231n/classifiers/linear_classifier.py`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "id": "sgd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 413.734891\n",
      "iteration 100 / 1500: loss 244.158811\n",
      "iteration 200 / 1500: loss 148.931623\n",
      "iteration 300 / 1500: loss 90.998185\n",
      "iteration 400 / 1500: loss 56.900887\n",
      "iteration 500 / 1500: loss 36.181521\n",
      "iteration 600 / 1500: loss 23.814009\n",
      "iteration 700 / 1500: loss 16.418085\n",
      "iteration 800 / 1500: loss 11.871949\n",
      "iteration 900 / 1500: loss 8.337993\n",
      "iteration 1000 / 1500: loss 7.214684\n",
      "iteration 1100 / 1500: loss 6.745641\n",
      "iteration 1200 / 1500: loss 6.203349\n",
      "iteration 1300 / 1500: loss 5.239610\n",
      "iteration 1400 / 1500: loss 4.992161\n",
      "That took 6.713802s\n"
     ]
    }
   ],
   "source": [
    "# In the file linear_classifier.py, implement SGD in the function\n",
    "# LinearClassifier.train() and then run it with the code below.\n",
    "from cs231n.classifiers import LinearSVM\n",
    "svm = LinearSVM()\n",
    "tic = time.time()\n",
    "loss_hist = svm.train(X_train, y_train, learning_rate=1e-7, reg=2.5e4,\n",
    "                      num_iters=1500, verbose=True)\n",
    "toc = time.time()\n",
    "print('That took %fs' % (toc - tic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A useful debugging strategy is to plot the loss as a function of\n",
    "# iteration number:\n",
    "plt.plot(loss_hist)\n",
    "plt.xlabel('Iteration number')\n",
    "plt.ylabel('Loss value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "id": "validate"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 0.383816\n",
      "validation accuracy: 0.380000\n"
     ]
    }
   ],
   "source": [
    "# Write the LinearSVM.predict function and evaluate the performance on both the\n",
    "# training and validation set\n",
    "y_train_pred = svm.predict(X_train)\n",
    "print('training accuracy: %f' % (np.mean(y_train == y_train_pred), ))\n",
    "y_val_pred = svm.predict(X_val)\n",
    "print('validation accuracy: %f' % (np.mean(y_val == y_val_pred), ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "id": "tuning",
    "tags": [
     "code"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_acc:0.3926122448979592  val_acc:0.382\n",
      "train_acc:0.39585714285714285  val_acc:0.398\n",
      "train_acc:0.4025918367346939  val_acc:0.409\n",
      "train_acc:0.399734693877551  val_acc:0.397\n",
      "train_acc:0.4001224489795918  val_acc:0.394\n",
      "train_acc:0.39638775510204083  val_acc:0.395\n",
      "train_acc:0.3952040816326531  val_acc:0.396\n",
      "train_acc:0.393  val_acc:0.401\n",
      "train_acc:0.385734693877551  val_acc:0.393\n",
      "train_acc:0.3892244897959184  val_acc:0.397\n",
      "train_acc:0.38946938775510204  val_acc:0.394\n",
      "train_acc:0.39108163265306123  val_acc:0.385\n",
      "train_acc:0.38740816326530614  val_acc:0.387\n",
      "train_acc:0.3897551020408163  val_acc:0.393\n",
      "train_acc:0.38912244897959186  val_acc:0.389\n",
      "train_acc:0.3944489795918367  val_acc:0.406\n",
      "train_acc:0.39010204081632655  val_acc:0.391\n",
      "train_acc:0.38742857142857146  val_acc:0.382\n",
      "train_acc:0.38051020408163266  val_acc:0.389\n",
      "train_acc:0.3902857142857143  val_acc:0.402\n",
      "train_acc:0.39171428571428574  val_acc:0.383\n",
      "train_acc:0.3812857142857143  val_acc:0.378\n",
      "train_acc:0.3828367346938776  val_acc:0.379\n",
      "train_acc:0.38012244897959185  val_acc:0.376\n",
      "train_acc:0.3739387755102041  val_acc:0.377\n",
      "train_acc:0.38351020408163267  val_acc:0.377\n",
      "train_acc:0.3877551020408163  val_acc:0.395\n",
      "train_acc:0.3786122448979592  val_acc:0.38\n",
      "train_acc:0.3746938775510204  val_acc:0.395\n",
      "train_acc:0.37555102040816324  val_acc:0.381\n",
      "train_acc:0.3805918367346939  val_acc:0.385\n",
      "train_acc:0.38448979591836735  val_acc:0.384\n",
      "train_acc:0.38110204081632654  val_acc:0.392\n",
      "train_acc:0.3775918367346939  val_acc:0.382\n",
      "train_acc:0.3723265306122449  val_acc:0.369\n",
      "train_acc:0.37510204081632653  val_acc:0.383\n",
      "lr 1.400000e-07 reg 7.000000e+03 train accuracy: 0.392612 val accuracy: 0.382000\n",
      "lr 1.400000e-07 reg 8.000000e+03 train accuracy: 0.399735 val accuracy: 0.397000\n",
      "lr 1.400000e-07 reg 9.000000e+03 train accuracy: 0.395204 val accuracy: 0.396000\n",
      "lr 1.400000e-07 reg 1.000000e+04 train accuracy: 0.389224 val accuracy: 0.397000\n",
      "lr 1.400000e-07 reg 1.100000e+04 train accuracy: 0.387408 val accuracy: 0.387000\n",
      "lr 1.400000e-07 reg 1.200000e+04 train accuracy: 0.394449 val accuracy: 0.406000\n",
      "lr 1.400000e-07 reg 1.700000e+04 train accuracy: 0.380510 val accuracy: 0.389000\n",
      "lr 1.400000e-07 reg 1.800000e+04 train accuracy: 0.381286 val accuracy: 0.378000\n",
      "lr 1.400000e-07 reg 1.900000e+04 train accuracy: 0.373939 val accuracy: 0.377000\n",
      "lr 1.400000e-07 reg 2.000000e+04 train accuracy: 0.378612 val accuracy: 0.380000\n",
      "lr 1.400000e-07 reg 2.100000e+04 train accuracy: 0.380592 val accuracy: 0.385000\n",
      "lr 1.400000e-07 reg 2.200000e+04 train accuracy: 0.377592 val accuracy: 0.382000\n",
      "lr 1.500000e-07 reg 7.000000e+03 train accuracy: 0.395857 val accuracy: 0.398000\n",
      "lr 1.500000e-07 reg 8.000000e+03 train accuracy: 0.400122 val accuracy: 0.394000\n",
      "lr 1.500000e-07 reg 9.000000e+03 train accuracy: 0.393000 val accuracy: 0.401000\n",
      "lr 1.500000e-07 reg 1.000000e+04 train accuracy: 0.389469 val accuracy: 0.394000\n",
      "lr 1.500000e-07 reg 1.100000e+04 train accuracy: 0.389755 val accuracy: 0.393000\n",
      "lr 1.500000e-07 reg 1.200000e+04 train accuracy: 0.390102 val accuracy: 0.391000\n",
      "lr 1.500000e-07 reg 1.700000e+04 train accuracy: 0.390286 val accuracy: 0.402000\n",
      "lr 1.500000e-07 reg 1.800000e+04 train accuracy: 0.382837 val accuracy: 0.379000\n",
      "lr 1.500000e-07 reg 1.900000e+04 train accuracy: 0.383510 val accuracy: 0.377000\n",
      "lr 1.500000e-07 reg 2.000000e+04 train accuracy: 0.374694 val accuracy: 0.395000\n",
      "lr 1.500000e-07 reg 2.100000e+04 train accuracy: 0.384490 val accuracy: 0.384000\n",
      "lr 1.500000e-07 reg 2.200000e+04 train accuracy: 0.372327 val accuracy: 0.369000\n",
      "lr 1.600000e-07 reg 7.000000e+03 train accuracy: 0.402592 val accuracy: 0.409000\n",
      "lr 1.600000e-07 reg 8.000000e+03 train accuracy: 0.396388 val accuracy: 0.395000\n",
      "lr 1.600000e-07 reg 9.000000e+03 train accuracy: 0.385735 val accuracy: 0.393000\n",
      "lr 1.600000e-07 reg 1.000000e+04 train accuracy: 0.391082 val accuracy: 0.385000\n",
      "lr 1.600000e-07 reg 1.100000e+04 train accuracy: 0.389122 val accuracy: 0.389000\n",
      "lr 1.600000e-07 reg 1.200000e+04 train accuracy: 0.387429 val accuracy: 0.382000\n",
      "lr 1.600000e-07 reg 1.700000e+04 train accuracy: 0.391714 val accuracy: 0.383000\n",
      "lr 1.600000e-07 reg 1.800000e+04 train accuracy: 0.380122 val accuracy: 0.376000\n",
      "lr 1.600000e-07 reg 1.900000e+04 train accuracy: 0.387755 val accuracy: 0.395000\n",
      "lr 1.600000e-07 reg 2.000000e+04 train accuracy: 0.375551 val accuracy: 0.381000\n",
      "lr 1.600000e-07 reg 2.100000e+04 train accuracy: 0.381102 val accuracy: 0.392000\n",
      "lr 1.600000e-07 reg 2.200000e+04 train accuracy: 0.375102 val accuracy: 0.383000\n",
      "best validation accuracy achieved during cross-validation: 0.409000\n"
     ]
    }
   ],
   "source": [
    "# Use the validation set to tune hyperparameters (regularization strength and\n",
    "# learning rate). You should experiment with different ranges for the learning\n",
    "# rates and regularization strengths; if you are careful you should be able to\n",
    "# get a classification accuracy of about 0.39 on the validation set.\n",
    "\n",
    "# Note: you may see runtime/overflow warnings during hyper-parameter search. \n",
    "# This may be caused by extreme values, and is not a bug.\n",
    "\n",
    "# results is dictionary mapping tuples of the form\n",
    "# (learning_rate, regularization_strength) to tuples of the form\n",
    "# (training_accuracy, validation_accuracy). The accuracy is simply the fraction\n",
    "# of data points that are correctly classified.\n",
    "results = {}\n",
    "best_val = -1   # The highest validation accuracy that we have seen so far.\n",
    "best_svm = None # The LinearSVM object that achieved the highest validation rate.\n",
    "\n",
    "################################################################################\n",
    "# TODO:                                                                        #\n",
    "# Write code that chooses the best hyperparameters by tuning on the validation #\n",
    "# set. For each combination of hyperparameters, train a linear SVM on the      #\n",
    "# training set, compute its accuracy on the training and validation sets, and  #\n",
    "# store these numbers in the results dictionary. In addition, store the best   #\n",
    "# validation accuracy in best_val and the LinearSVM object that achieves this  #\n",
    "# accuracy in best_svm.                                                        #\n",
    "#                                                                              #\n",
    "# Hint: You should use a small value for num_iters as you develop your         #\n",
    "# validation code so that the SVMs don't take much time to train; once you are #\n",
    "# confident that your validation code works, you should rerun the validation   #\n",
    "# code with a larger value for num_iters.                                      #\n",
    "################################################################################\n",
    "\n",
    "# Provided as a reference. You may or may not want to change these hyperparameters\n",
    "# learning_rates = [1e-7, 5e-5]\n",
    "# regularization_strengths = [2.5e4, 5e4]\n",
    "learning_rates = [1.4e-7, 1.5e-7, 1.6e-7]\n",
    "regularization_strengths = [(1+i*0.1)*1e4 for i in range(-3,3)] + [(2+0.1*i)*1e4 for i in range(-3,3)]\n",
    "\n",
    "# *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "for rs in regularization_strengths:\n",
    "    for lr in learning_rates:\n",
    "        svm = LinearSVM()\n",
    "        loss_hist = svm.train(X_train,y_train,lr,rs,num_iters=3000)\n",
    "        y_train_pred = svm.predict(X_train)\n",
    "        train_acc = np.mean(y_train == y_train_pred)\n",
    "        y_val_pred = svm.predict(X_val)\n",
    "        val_acc = np.mean(y_val == y_val_pred)\n",
    "        if val_acc > best_val:\n",
    "            best_val = val_acc\n",
    "            best_svm = svm\n",
    "        results[(lr,rs)] = train_acc,val_acc\n",
    "        print(\"train_acc:{}  val_acc:{}\".format(train_acc,val_acc))\n",
    "pass\n",
    "\n",
    "# *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    \n",
    "# Print out results.\n",
    "for lr, reg in sorted(results):\n",
    "    train_accuracy, val_accuracy = results[(lr, reg)]\n",
    "    print('lr %e reg %e train accuracy: %f val accuracy: %f' % (\n",
    "                lr, reg, train_accuracy, val_accuracy))\n",
    "    \n",
    "print('best validation accuracy achieved during cross-validation: %f' % best_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the cross-validation results\n",
    "import math\n",
    "import pdb\n",
    "\n",
    "# pdb.set_trace()\n",
    "\n",
    "x_scatter = [math.log10(x[0]) for x in results]\n",
    "y_scatter = [math.log10(x[1]) for x in results]\n",
    "\n",
    "# plot training accuracy\n",
    "marker_size = 100\n",
    "colors = [results[x][0] for x in results]\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.tight_layout(pad=3)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap=plt.cm.coolwarm)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 training accuracy')\n",
    "\n",
    "# plot validation accuracy\n",
    "colors = [results[x][1] for x in results] # default size of markers is 20\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap=plt.cm.coolwarm)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 validation accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "id": "test"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linear SVM on raw pixels final test set accuracy: 0.388000\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the best svm on test set\n",
    "y_test_pred = best_svm.predict(X_test)\n",
    "test_accuracy = np.mean(y_test == y_test_pred)\n",
    "print('linear SVM on raw pixels final test set accuracy: %f' % test_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the learned weights for each class.\n",
    "# Depending on your choice of learning rate and regularization strength, these may\n",
    "# or may not be nice to look at.\n",
    "w = best_svm.W[:-1,:] # strip out the bias\n",
    "w = w.reshape(32, 32, 3, 10)\n",
    "w_min, w_max = np.min(w), np.max(w)\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "for i in range(10):\n",
    "    plt.subplot(2, 5, i + 1)\n",
    "      \n",
    "    # Rescale the weights to be between 0 and 255\n",
    "    wimg = 255.0 * (w[:, :, :, i].squeeze() - w_min) / (w_max - w_min)\n",
    "    plt.imshow(wimg.astype('uint8'))\n",
    "    plt.axis('off')\n",
    "    plt.title(classes[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Inline question 2**\n",
    "\n",
    "Describe what your visualized SVM weights look like, and offer a brief explanation for why they look they way that they do.\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$ SVM权重的外观好像对应物体的平均值。在训练中我们调整权重，使权重向loss变小的指引方向上调整。因此预测不同物体的参数会向其预测物体的方向调整，最终好像他们的平均值\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
